This paper is a new approach to improve road safety and traffic flow by combining vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. The Study is focused on a system that connects vehicles with each other and with traffic light to share real-time data about speed and position.
This work is aimed to discuss the methodology adopted for developing a system which predicts and advises the optimal speed for vehicles approaching an intersection. Inspired by the Green Light Optimized Speed Advisory (GLOSA) , the proposed system is designed to help drivers approach traffic signals at speeds that minimize unnecessary stops, reduce delays, and improve traffic efficiency. This paper contains the approach taken, the decision-making algorithm, and the simulation framework built in MATLAB/Simulink to validate the concept under real traffic conditions. Simulation results are presented to demonstrate how the system generates speed recommendations based on vehicle parameters and traffic light states.
We have worked on the integration of both V2V and V2I communications, combined with a speed advisory algorithm. This work paves the way for smarter, more responsive traffic management systems and supports the future deployment of connected and autonomous vehicles.